Driven by the digitalization in the consumer video and photo market as well as by the increasing capacity of re-writable storage devices such as hard discs and DVD, the problem of digital asset management drifts from the professional to the consumer market.
One of the challenges of video and photo asset management is to gather semantic information from the media in order to allow for easy data access. In the professional market, first products propose semantic access.
This invention addresses the problem of semantic access to personal video and photo assets for the consumer market.
Known consumer tools for image browsing are usually based on available metadata such as date of digitalization and film number, or based on manually added keywords and annotations such as source/author or place/time. The first type of metadata allows only for poor browsing capabilities while the second type of metadata needs to be inserted manually and the resulting browsing capabilities depend heavily on metadata quality and quantity.
One solution to raise the performance of consumer tools for image browsing is to add automatically identified semantic elements such as “persons”, “indoor scene” or “mountains” as known from very recent professional tools. But such a core solution is not adapted to inexperienced users of consumer electronic products. In this market, image access is not always guided by a clear objective or a predefined workflow. A professional user may look precisely for an image of a person in an indoor scene, while an inexperienced user may look initially for the photo of a person and, after having seen the photos of some persons, may look for mountain images because these persons recall him the memory of a mountain trip. Like “zapping” for TV watching, the user perceives video and photo browsing as divertissement. Initial browsing objectives are changed while browsing.